DISTRIBUTED ONLINE LEARNING FOR PRIVACY-PRESERVING PERSONAL PREDICTIVE MODELS

摘要

Methods, apparatus, systems, and computer program products are provided for providing distributed online learning for personal predictive models that preserves user privacy. An example method comprises receiving model updates based at least in part on synchronization metadata. The model update comprises one or more received model parameter updates. The received model parameter updates correspond to one or more model parameters. The model updates are associated with a particular apparatus. The example method further comprises determining a decay factor based at least in part on the synchronization metadata; applying the decay factor to the one or more received model parameter updates; and updating the one or more model parameters based on the decayed model parameter updates.